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IEICE TRANSACTIONS on Fundamentals

Ball State Based Parallel Ball Tracking and Event Detection for Volleyball Game Analysis

Xina CHENG, Norikazu IKOMA, Masaaki HONDA, Takeshi IKENAGA

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Summary :

The ball state tracking and detection technology plays a significant role in volleyball game analysis, whose performance is limited due to the challenges include: 1) the inaccurate ball trajectory; 2) multiple numbers of the ball event category; 3) the large intra-class difference of one event. With the goal of broadcasting supporting for volleyball games which requires a real time system, this paper proposes a ball state based parallel ball tracking and event detection method based on a sequential estimation method such as particle filter. This method employs a parallel process of the 3D ball tracking and the event detection so that it is friendly for real time system implementation. The 3D ball tracking process uses the same models with the past work [8]. For event detection process, a ball event change estimation based multiple system model, a past trajectory referred hit point likelihood and a court-line distance feature based event type detection are proposed. First, the multiple system model transits the ball event state, which consists the event starting time and the event type, through three models dealing with different ball motion situations in the volleyball game, such as the motion keeping and changing. The mixture of these models is decided by estimation of the ball event change estimation. Secondly, the past trajectory referred hit point likelihood avoids the processing time delay between the ball tracking and the event detection process by evaluating the probability of the ball being hit at certain time without using future ball trajectories. Third, the feature of the distance between the ball and the specific court line are extracted to detect the ball event type. Experimental results based on multi-view HDTV video sequences (2014 Inter High School Men's Volleyball Games, Japan), which contains 606 events in total, show that the detection rate reaches 88.61% while the success rate of 3D ball tracking keeps more than 99%.

Publication
IEICE TRANSACTIONS on Fundamentals Vol.E100-A No.11 pp.2285-2294
Publication Date
2017/11/01
Publicized
Online ISSN
1745-1337
DOI
10.1587/transfun.E100.A.2285
Type of Manuscript
Special Section PAPER (Special Section on Smart Multimedia & Communication Systems)
Category
Vision

Authors

Xina CHENG
  Waseda University
Norikazu IKOMA
  the Nippon Institute of Technology
Masaaki HONDA
  Waseda University
Takeshi IKENAGA
  Waseda University

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